局部平稳部分线性面板数据模型的统计推断

部分线性模型是一类非常重要的半参数回归模型,由于它既含有参数部分又含有非参数部分,与常规的线性模型相比具有更强的适应性和解释能力。文章研究带有局部平稳协变量的固定效应部分线性面板数据模型的统计推断。首先提出一个两阶段估计方法得到模型中未知参数和非参数函数的估计,并证明估计量的渐近性质,然后运用不变原理构造出非参数函数的一致置信带,最后通过数值模拟研究和实例分析验证了该方法的有效性。     

农地产权结构变迁视域下土地增值收益的公平分享

农地产权结构是搭建土地增值收益分配与宪法秩序有效链接的重要桥梁.从农地产权结构变迁的视角看,我国传统土地增值收益的国有化机制实际在很大程度上符合1982年宪法所确立的社会主义地租国有原则及地利共享秩序.然而,由于宪法土地条款一开始就被注入了地利分配具有倾向性的思想基因,长此以往便忽视了农民作为整体分享土地增值收益的"另一半宪法秩序".新型城镇化背景下,国家进行了"同地同权"、赋权于"民"的农村土地管理制度改革,其实质是宪法秩序的延续而非替代,我国土地增值收益分配的主要机制仍是征地补偿制度.要实现我国土地增值收益的公平分享,必须回到社会主义"国家—集体"一元论的完整地利共享秩序中来,并遵循实质平等的要求,通过以"人的城镇化"为目标对区片综合地价进行限定、采取倾向于农村及农业发展的"土地财政"政策、打破城乡户籍二元制实现城乡一体化发展等方案,推动农民全过程参与、共享土地利益.     

实物资金流量表的预测方法研究

资金流量表是国民经济核算体系中的重要组成部分。然而，由于在编制过程中需要采集大量的数据，通常情况下，很多国家的资金流量表都会有较长时间的滞后。在编制实物资金流量表的延长表时，已有方法通常是基于基期与预测期交易收支结构保持不变的假定条件。然而，经济结构发生显著变化时，该类方法就会失效。基于上述问题，研究弱化模型的假设条件，并提出了新的实物资金流量表预测方法( 简称 FPTF方法)。根据表中元素必须满足的约束条件，该方法通过建立数学模型解除约束，其次基于历史数据的动态趋势，采用适当的时间序列分析方法来预测目标年份的实物资金流量表。通过仿真分析，验证了所提方法的有效性和稳定性。此外，基于中国1992年～2014 年的实物资金流量表数据进行实例分析，取得了满意的分析结果。     

The ‘right time’ – negotiating the timing of interviews with vulnerable young people

Participant retention is a key factor in determining the success of longitudinal research. Challenges in re-locating and retaining participants over the long term are major issues for researchers working with young people who face adversity and experience frequent changes in circumstances. This article reports on a study of vulnerable young people and their transition into adulthood. Rather than the more conventional schedule-based approach to locating and re-interviewing young people, a relational process, the ‘right time’ framework, was used to facilitate young people's involvement in the study. Embedded in the ‘right time’ framework is recognition of the diverse and fluctuating circumstances that shape young people's availability for interviews. Several case examples are considered which amplify the way that the ‘right time’ framework allowed the research to navigate around these circumstances. The case examples highlight the value young people attached to being involved in the research, the influence on the ‘right time’ of wider relational tensions for young people and the need to negotiate researcher status as a different sort of adult. The ‘right time’ framework contributed to a high retention rate in the study generating a more representative sample and enhancing the subsequent data analysis by providing valuable insights into the lives of these vulnerable young people.     

论贤相伊尹的个人素质及其形成

伊尹作为中国历史上第一位贤相,其突出的个人素质表现在精于至味之理、精通耕作之道、创制治病汤液几方面,即懂得如何吃饭、种地和治病。这正是广大民众最为关心的事情,也是治理内政极其关键的因素,只有这三件事做得好,才可能完成"祀与戎"等国家大事。如此全面素质的形成,与其丰富的人生经历和勤于思索有关。     

Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

Linear scalar-on-surface random effects regression models

Many research fields increasingly involve analyzing data of a complex structure. Models investigating the dependence of a response on a predictor have moved beyond the ordinary scalar-on-vector regression. We propose a regression model for a scalar response and a surface (or a bivariate function) predictor. The predictor has a random component and the regression model falls in the framework of linear random effects models. We estimate the model parameters via maximizing the log-likelihood with the ECME (Expectation/Conditional Maximization Either) algorithm. We use the approach to analyze a data set where the response is the neuroticism score and the predictor is the resting-state brain function image. In the simulations we tried, the approach has better performance than two other approaches, a functional principal component regression approach and a smooth scalar-on-image regression approach.     

The evolution of intellectual property strategy in innovation ecosystems: Uncovering complementary and substitute appropriability regimes

In this article, we attempt to extend and nuance the debate on intellectual property (IP) strategy, appropriation, and open innovation in dynamic and systemic innovation contexts. We present the case of four generations of mobile telecommunications systems (covering the period 1980–2015), and describe and analyze the co-evolution of strategic IP management and innovation ecosystems. Throughout this development, technologies and technological relationships were governed with different and shifting degrees of formality. Simultaneously, firms differentiated technology accessibility across actors and technologies to benefit from openness and appropriation of innovation. Our analysis shows that the discussion of competitiveness and appropriability needs to be expanded from the focal appropriability regime and complementary assets to the larger context of the innovation ecosystem and its cooperative and competitive actor relations, with dispersed complementary and substitute assets and technologies. Consequently, the shaping of complementary and substitute appropriability regimes is central when strategizing in dynamic and systemic innovation contexts. This holds important implications for the management of open innovation, innovation ecosystems, platforms, and coopetition.     

为合法经营活动而侵犯公民个人信息的刑法规制

最高人民法院、最高人民检察院《关于办理侵犯公民个人信息刑事案件适用法律若干问题的解释》第六条对为合法经营活动而侵犯公民个人信息行为进行独立规制,是新型犯罪罪状表述抽象化与罪状解释具体化、信息时代信息价值多元化与危害行为多样化、现代社会犯罪治理精细化与刑法评价精准化的内在要求.为合法经营活动而侵犯公民个人信息行为相关规范要素中的“为合法经营活动”应理解为主观超过要素,“获利五万元”应作严格解释,“曾因侵犯公民个人信息”应作广义解释,“其他情节严重”应包括信息数量标准.